Big Data Analysis: Techniques, Challenges, and Business Support

This report discusses the concept of big data analysis, its characteristics, challenges, and techniques. It also explains how big data technology can support business operations with examples. The report is relevant to the subject of Information Systems and Big Data Analysis (BMP4005) and is suitable for college and university students.

Business Management
BMP4005
Information Systems and Big Data Analysis
Poster and Accompanying Paper
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Table of Contents
Introduction................................................................................................................................4
What big data is and the characteristics of big data ............................................................4
The challenges of big data analytic.......................................................................................5
The techniques that are currently available to analyses big data........................................6
How Big Data technology could support business, an explanation with examples .............6
Poster.....................................................................................................................................7
Conclusion .................................................................................................................................7
References .................................................................................................................................7
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Introduction
The big data analysis is process of examining large and complex data which is used
for disclosing the data such as correlation customer preferences, hidden patters and market
trends. From the large set of data this tool is used for analyzing and extracting information
which helps company in making better decision and valuable insights is offered that reduces
organization risk. The concept of information system is wide in the economy as organization
are interrelated with IT sector that provides wide range of solutions. The information system
make use of internet which is associated with network of devices for having connectivity and
exchange of data (Liu, Z and et.al., 2017). The communication network is build with the use
of information technology for organization and by creating and administering databases the
information is safeguard. The use of information system in companies is to have interaction
with customers, conduct business transactions, manage the organization, and so on. In the
report the discussion is of big data and characteristics. Challenges along with techniques of
big data is considered of big data analysis. Further, there is a description of how big data
technology will support business.
What big data is and the characteristics of big data
This process is a type of advanced analysis that includes complex applications along
with components such as statistical algorithms, predictive models, and so on. The design of
big data analytics is to help a company make data-driven decisions that will improve business
results. Big data is defined as the analysis and extraction of information that can also be used
for predictive and user-analytical behaviour. The use of big data in companies helps improve
business operations and provide better services to its customers, which increases the
company's overall bottom line and revenue. The large amount of data is collected which is
too complex to be interpreted by humans or traditional data sets (Pramanik and et.al, 2017).
Analysing big data makes it easier for companies to support their information and use it to
find new opportunities that lead to smarter management of the company. In this way, it
generates higher profits, makes operations in the company more efficient and makes its
potential customers happy. Big data includes data analysis, data visualization, data storage,
data mining, etc. Following are the characteristics of big data-
 Volume- Big data technology processes large amounts of data related to large
amounts of data obtained from multiple daily sources such as machines, social media
and networks, etc.
 Velocity- This is refereed as speed which is related to generation of information and
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process of data processing is created. The flow of data is at high speed from several
sources such as application logs, social media sites etc.
 Variety- The term defines to different sources and their nature for extracting data. In
the past spreadsheets and databases were use foe collecting information while in
modern times there is use of e-mails, photos, PDF through which data are stored and
analyzed.
 Veracity- It is associated with reliability and trustworthiness of data by having
several ways of data translation. It defines to accuracy of data. In the big data only
data quality is not considered but also considers trustworthy, its type, source and data
process (Roccetti, M and et.al., 2020).
 Value- This is related to advantage derived from the data. The data needs to valuable
and reliable for analyses or processing. The data is considered to valuable after
successful analysis if data sets and helping in storing, processing and analyzing data.
The company can bear loss in revenue due to poor quality of data.
The challenges of big data analytic
Big data challenges involve finding the best way to manage large amounts of data,
including storing and analysing information in multiple data stores. There are several major
challenges when dealing with big data. Some of these challenges are explained as follows:
 Lack of understanding of complex data- The lack of appropriate understanding
makes the firm fails in its initiation of big data. Without having proper information of
data base it cannot be used properly for storage and company might known its
importance, source and data process which creates difficulty in understanding
complex data that cannot be recover easily. To address such challenges, companies
can organize workshops, seminars, and training programs to impart understanding of
data at all levels of the organization.
 Integration of data from different sources- The data is acquired from different
sources like customer logs, presentations, financial reports, social media etc. This
becomes challenging task for the company to comply data from all such different
sources and organising it in final report (Sik, D and et.al., 2017).
 Securing data- The company also face a challenge of securing complex data of
numerous amount. Companies are concerned with understanding, analysing and
storing the information from data sets and promoting data security for later phases.
This is not a healthy path as unprotected data could become a breeding ground for
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malicious hackers.
The techniques that are currently available to analyses big data
Organizations use a variety of data management techniques and need more insight
into speed, scope, and depth. There are several techniques for analyzing big data, which are
mentioned below:
 Machine learning: This technique helps in analysis of big data which can be made
more understandable by displaying more trends and patterns. The technique of
machine learning benefits in accelerating the procedure by use of algorithms for
decision making. It facilitates in the classification of upcoming information,
identification of trend & patterns and data is converted in visualize form. This also
gives prediction which cannot be provided by human analysts.
 A/B testing: This technique is a originally randomized control experiment that
provides a way of comparing the two variants of a version to identify better
performers in a controlled environment. Successful A / B testing technique leads to
great benefits and a large volume of business for the company.
 Statistics: When analyzing big data, the role of this technique is to collect, organize,
and infer the data through research methods such as base surveys and experiments.
Statistical technique makes it easy to analyze big data by inferring understanding
about implicit data sets or the fact that it is trying to explain.
How Big Data technology could support business, an explanation with
examples
Big data technology offers new opportunities for business growth from the internal
view to the interactions of customers or users who are at the front. With the help of robot-
controlled process automation, big data improves intrinsic efficiency and business operations.
Large amounts of data can be perfectly analysed and further developed in business processes
for automated decision-making. Big data can also be used to reveal hidden opportunities that
the company is not aware of in order to verify numerous data sets. Massive data sets are also
used in the development of new products or help in the innovation of existing products. The
use of big data in business is crucial for companies to gain competitive advantage (Wang and
et.al, 2020). In many industries, existing rivalries and new firms are leveraging data-driven
techniques to capture, innovate, and compete. For example, data pioneers in healthcare
analyse the results of pharmaceuticals. Companies focus on identifying benefits and dangers
that are not clearly defined at the time of initial clinical trials. In this situation, big data helps
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to better analyse studies and determine interpretations. In this way, big data technology helps
power a company's business. The big data offers new perspective for companies to discover
information which can be utilised in appropriate way.
 Better decision making- This is a tool used in company for making intelligent
decisions that are based on information and not on assumptions. For improving
decision the company is required to access data so that user can analyze and enquiry
data to response business questions. Walmart, which gave people controlled access to
data, can serve as an example.
 Drive customer acquisition and retention- The customer is a valuable asset for the
company because big data is used to observe consumer-related patterns and trends.
The more data a company collects, the more patterns and trends can be identified.
Modern technology is helping to collect consumer data and strategies are being
developed from big data to maintain the customer base. Customer needs are met
through understanding customer insights. One example is Coca-Cola, which has
managed to strengthen its data strategy by creating a digital Led-loyally program.
Poster
Conclusion
It is being concluded, big data combine all tools along with process which is relevant
while using and managing data sets of large amounts. In the present report the challenges of
big data analytics are been seen and companies are required for making solutions of such
challenges to overcome with this. There are several techniques of big data which are used in
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organisation for managing the information properly in organised way to make it easy
understandable. The big data creates data sets quickly by assembling unique information
system and availability of hardware and software in history of data analysis.
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References
Liu, Z and et.al., 2017. Practical-oriented protocols for privacy-preserving outsourced big
data analysis: Challenges and future research directions. Computers & Security, 69,
pp.97-113.
Pramanik and et.al, 2017. Big data analytics for security and criminal investigations. Wiley
interdisciplinary reviews: data mining and knowledge discovery. 7(4). p.e1208.
Roccetti, M and et.al., 2020. A Cautionary Tale for Machine Learning Design: why we Still
Need Human-Assisted Big Data Analysis. Mobile Networks & Applications, 25(3).
Sik, D and et.al., 2017, September. Implementation of a geographic information system with
big data environment on common data model. In 2017 8th IEEE International
Conference on Cognitive Infocommunications (CogInfoCom) (pp. 000181-000184).
IEEE.
Sun and et.al, 2020. Big data analytics for venture capital application: towards innovation
performance improvement. International Journal of Information Management. 50.
pp.557-565.
Wang and et.al, 2020. Big data analytics on enterprise credit risk evaluation of e-Business
platform. Information Systems and e-Business Management. 18(3). pp.311-350.
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